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Registro Completo |
Biblioteca(s): |
Embrapa Mandioca e Fruticultura; Embrapa Semiárido. |
Data corrente: |
14/08/2017 |
Data da última atualização: |
08/01/2020 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
OLIVEIRA, E. J. de; MORGANTE, C. V.; AIDAR, S. de T.; CHAVES, A. R. de M.; ANTONIO, R. P.; CRUZ, J. L.; COELHO FILHO, M. A. |
Afiliação: |
EDER JORGE DE OLIVEIRA, CNPMF; CAROLINA VIANNA MORGANTE, CPATSA; SAULO DE TARSO AIDAR, CPATSA; AGNALDO RODRIGUES DE MELO CHAVES, CPATSA; RAFAELA PRISCILA ANTONIO, CPATSA; JAILSON LOPES CRUZ, CNPMF; MAURICIO ANTONIO COELHO FILHO, CNPMF. |
Título: |
Evaluation of cassava germplasm for drought tolerance under field conditions. |
Ano de publicação: |
2017 |
Fonte/Imprenta: |
Euphytica, v. 213, n. 8, aug. 2017. |
DOI: |
10.1007/s10681-017-1972- |
Idioma: |
Inglês |
Conteúdo: |
The development of cassava (Manihot esculenta Crantz) with a high yield under water-deficit conditions is one of the goal of the breeding programs. The objective of this study was to evaluate the performance and to select cassava accessions based on drought tolerance indices and productive potential under water stress. Forty-nine accessions were evaluated for five agronomic traits (plant height?PH, root yield?RoY, shoot yield?ShY, harvest index?HI; and dry matter content of roots?DMC) under full irrigation conditions and drought stress (DS). The accessions were selected based on: (i) high yield under drought conditions (HY-DS) and (ii) high drought tolerance (Dr-To) based on six different indices. Overall, water stress dramatically reduced the traits? means (RoY?72.98%, ShY?54.95%, DMC?26.15%, HI?31.05%, and PH?32.95%). Low coincidence among the top ten accessions was identified based on HY-DS and Dr-To criteria. Therefore, considering only the most important traits (RoY andShY), five accessions (BGM0815, BGM0598, 9624-09, BGM0818, and BRS Formosa) presented high HY-DS. In contrast, to Dr-To criterion, eight and nine accessions were selected for high yield of the aerial part (ShY and PH) and roots (RoY and DMC), respectively. The mean productivity, geometric mean productivity, and drought tolerance indices were the most promising to identify genotypes with high agronomic attributes, while drought susceptibility index, susceptibility, and yield stability index were suitable to identify the most drought tolerant accessions. This set of selected accessions can be used in breeding programs aimed at high yield and drought tolerance. MenosThe development of cassava (Manihot esculenta Crantz) with a high yield under water-deficit conditions is one of the goal of the breeding programs. The objective of this study was to evaluate the performance and to select cassava accessions based on drought tolerance indices and productive potential under water stress. Forty-nine accessions were evaluated for five agronomic traits (plant height?PH, root yield?RoY, shoot yield?ShY, harvest index?HI; and dry matter content of roots?DMC) under full irrigation conditions and drought stress (DS). The accessions were selected based on: (i) high yield under drought conditions (HY-DS) and (ii) high drought tolerance (Dr-To) based on six different indices. Overall, water stress dramatically reduced the traits? means (RoY?72.98%, ShY?54.95%, DMC?26.15%, HI?31.05%, and PH?32.95%). Low coincidence among the top ten accessions was identified based on HY-DS and Dr-To criteria. Therefore, considering only the most important traits (RoY andShY), five accessions (BGM0815, BGM0598, 9624-09, BGM0818, and BRS Formosa) presented high HY-DS. In contrast, to Dr-To criterion, eight and nine accessions were selected for high yield of the aerial part (ShY and PH) and roots (RoY and DMC), respectively. The mean productivity, geometric mean productivity, and drought tolerance indices were the most promising to identify genotypes with high agronomic attributes, while drought susceptibility index, susceptibility, and yield stability index were suitable t... Mostrar Tudo |
Palavras-Chave: |
Deficit de água; Germplasma; Tolerância a seca; Water deficit. |
Thesagro: |
Mandioca; Manihot Esculenta. |
Thesaurus Nal: |
Cassava; Drought tolerance; Plant breeding. |
Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/162681/1/Carolina-2017.pdf
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Marc: |
LEADER 02533naa a2200313 a 4500 001 2074005 005 2020-01-08 008 2017 bl uuuu u00u1 u #d 024 7 $a10.1007/s10681-017-1972-$2DOI 100 1 $aOLIVEIRA, E. J. de 245 $aEvaluation of cassava germplasm for drought tolerance under field conditions.$h[electronic resource] 260 $c2017 520 $aThe development of cassava (Manihot esculenta Crantz) with a high yield under water-deficit conditions is one of the goal of the breeding programs. The objective of this study was to evaluate the performance and to select cassava accessions based on drought tolerance indices and productive potential under water stress. Forty-nine accessions were evaluated for five agronomic traits (plant height?PH, root yield?RoY, shoot yield?ShY, harvest index?HI; and dry matter content of roots?DMC) under full irrigation conditions and drought stress (DS). The accessions were selected based on: (i) high yield under drought conditions (HY-DS) and (ii) high drought tolerance (Dr-To) based on six different indices. Overall, water stress dramatically reduced the traits? means (RoY?72.98%, ShY?54.95%, DMC?26.15%, HI?31.05%, and PH?32.95%). Low coincidence among the top ten accessions was identified based on HY-DS and Dr-To criteria. Therefore, considering only the most important traits (RoY andShY), five accessions (BGM0815, BGM0598, 9624-09, BGM0818, and BRS Formosa) presented high HY-DS. In contrast, to Dr-To criterion, eight and nine accessions were selected for high yield of the aerial part (ShY and PH) and roots (RoY and DMC), respectively. The mean productivity, geometric mean productivity, and drought tolerance indices were the most promising to identify genotypes with high agronomic attributes, while drought susceptibility index, susceptibility, and yield stability index were suitable to identify the most drought tolerant accessions. This set of selected accessions can be used in breeding programs aimed at high yield and drought tolerance. 650 $aCassava 650 $aDrought tolerance 650 $aPlant breeding 650 $aMandioca 650 $aManihot Esculenta 653 $aDeficit de água 653 $aGermplasma 653 $aTolerância a seca 653 $aWater deficit 700 1 $aMORGANTE, C. V. 700 1 $aAIDAR, S. de T. 700 1 $aCHAVES, A. R. de M. 700 1 $aANTONIO, R. P. 700 1 $aCRUZ, J. L. 700 1 $aCOELHO FILHO, M. A. 773 $tEuphytica$gv. 213, n. 8, aug. 2017.
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Embrapa Semiárido (CPATSA) |
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![](/consulta/web/img/deny.png) | Acesso ao texto completo restrito à biblioteca da Embrapa Solos. Para informações adicionais entre em contato com cnps.biblioteca@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Arroz e Feijão; Embrapa Solos. |
Data corrente: |
10/01/2007 |
Data da última atualização: |
16/09/2021 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
Internacional - A |
Autoria: |
BENITES, V. de M.; MACHADO, P. L. O. de A.; FIDALGO, E. C. C.; COELHO, M. R.; MADARI, B. E. |
Afiliação: |
VINICIUS DE MELO BENITES, CNPS; PEDRO LUIZ OLIVEIRA DE A MACHADO, CNPAF; ELAINE CRISTINA CARDOSO FIDALGO, CNPS; MAURICIO RIZZATO COELHO, CNPS; BEATA EMOKE MADARI, CNPAF. |
Título: |
Pedotransfer functions for estimating soil bulk density from existing soil survey reports in Brazil. |
Ano de publicação: |
2007 |
Fonte/Imprenta: |
Geoderma, v. 139, n. 1/2, p. 90-97, Apr. 2007. |
DOI: |
https://doi.org/10.1016/j.geoderma.2007.01.005 |
Idioma: |
Inglês |
Conteúdo: |
Soil bulk density (Db) measurement is essential to estimate soil carbon reserves. However, field sampling, specially at depth, and direct measurement of Db is labor intensive, tedious and often impractical. Thus regression models or pedotransfer functions (PTFs) based on easily measured soil properties are an alternative for laborious Db measurements. A forward stepwise multiple regression routine was used to predict Db from 17 soil properties using a data set (data set 1) constructed from the Soil Archives of Embrapa Solos, Rio de Janeiro, Brazil. A first exploratory regression model using 1002 soil samples of data set 1 led to the development of a model, which indicated that total nitrogen (N), clay content (Clay) and sum of basic cations (SB) were the three strongest contributors to Db prediction (Adjusted-R2=0.71, Standard error of the estimate=0.10). A simplified regression model was developed using easily-measured soil attributes, such as soil organic carbon (TOC), Clay and SB. This model described 66% of the variation of Db in 1396 soil samples distributed at all depths (Standard error of the estimate=0.11). Clay content showed a good correlation with predicted Db (Beta value=-0.58) followed by TOC (Beta value=-0.51) and SB (Beta value=0.21). Partitioning the data set 1 into groups by soil depth (0?30 and 30?100 cm) and soil order (Latossolos and Argissolos) did not improve the accuracy of regression equations. In addition, we tested the Db predictive potential of the proposed model and three existing models (two from Brazil and one from the US) on an independent soil data set (data set 2). A general overestimation of predicted Db by the US model, with mean predicted error (MPE) of 0.11 shows that published PTFs developed on different environments should be used with care. Existing Brazilian models developed for the Amazon biome, on the other hand, were found to produce a slight underestimation with MPE values ranging from -0.03 to -0.16. The proposed simple regression model including Clay, TOC and SB was observed to be the most accurate and least biased. MenosSoil bulk density (Db) measurement is essential to estimate soil carbon reserves. However, field sampling, specially at depth, and direct measurement of Db is labor intensive, tedious and often impractical. Thus regression models or pedotransfer functions (PTFs) based on easily measured soil properties are an alternative for laborious Db measurements. A forward stepwise multiple regression routine was used to predict Db from 17 soil properties using a data set (data set 1) constructed from the Soil Archives of Embrapa Solos, Rio de Janeiro, Brazil. A first exploratory regression model using 1002 soil samples of data set 1 led to the development of a model, which indicated that total nitrogen (N), clay content (Clay) and sum of basic cations (SB) were the three strongest contributors to Db prediction (Adjusted-R2=0.71, Standard error of the estimate=0.10). A simplified regression model was developed using easily-measured soil attributes, such as soil organic carbon (TOC), Clay and SB. This model described 66% of the variation of Db in 1396 soil samples distributed at all depths (Standard error of the estimate=0.11). Clay content showed a good correlation with predicted Db (Beta value=-0.58) followed by TOC (Beta value=-0.51) and SB (Beta value=0.21). Partitioning the data set 1 into groups by soil depth (0?30 and 30?100 cm) and soil order (Latossolos and Argissolos) did not improve the accuracy of regression equations. In addition, we tested the Db predictive potential of the... Mostrar Tudo |
Palavras-Chave: |
Carbono orgânico do solo; Clay content; Funções de pedotransferência; Validação do modelo. |
Thesagro: |
Argila; Carbono; Solo; Solo Orgânico. |
Thesaurus NAL: |
Clay; Model validation; Pedotransfer functions; Soil organic carbon. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
Marc: |
LEADER 03082naa a2200325 a 4500 001 1339174 005 2021-09-16 008 2007 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.1016/j.geoderma.2007.01.005$2DOI 100 1 $aBENITES, V. de M. 245 $aPedotransfer functions for estimating soil bulk density from existing soil survey reports in Brazil.$h[electronic resource] 260 $c2007 520 $aSoil bulk density (Db) measurement is essential to estimate soil carbon reserves. However, field sampling, specially at depth, and direct measurement of Db is labor intensive, tedious and often impractical. Thus regression models or pedotransfer functions (PTFs) based on easily measured soil properties are an alternative for laborious Db measurements. A forward stepwise multiple regression routine was used to predict Db from 17 soil properties using a data set (data set 1) constructed from the Soil Archives of Embrapa Solos, Rio de Janeiro, Brazil. A first exploratory regression model using 1002 soil samples of data set 1 led to the development of a model, which indicated that total nitrogen (N), clay content (Clay) and sum of basic cations (SB) were the three strongest contributors to Db prediction (Adjusted-R2=0.71, Standard error of the estimate=0.10). A simplified regression model was developed using easily-measured soil attributes, such as soil organic carbon (TOC), Clay and SB. This model described 66% of the variation of Db in 1396 soil samples distributed at all depths (Standard error of the estimate=0.11). Clay content showed a good correlation with predicted Db (Beta value=-0.58) followed by TOC (Beta value=-0.51) and SB (Beta value=0.21). Partitioning the data set 1 into groups by soil depth (0?30 and 30?100 cm) and soil order (Latossolos and Argissolos) did not improve the accuracy of regression equations. In addition, we tested the Db predictive potential of the proposed model and three existing models (two from Brazil and one from the US) on an independent soil data set (data set 2). A general overestimation of predicted Db by the US model, with mean predicted error (MPE) of 0.11 shows that published PTFs developed on different environments should be used with care. Existing Brazilian models developed for the Amazon biome, on the other hand, were found to produce a slight underestimation with MPE values ranging from -0.03 to -0.16. The proposed simple regression model including Clay, TOC and SB was observed to be the most accurate and least biased. 650 $aClay 650 $aModel validation 650 $aPedotransfer functions 650 $aSoil organic carbon 650 $aArgila 650 $aCarbono 650 $aSolo 650 $aSolo Orgânico 653 $aCarbono orgânico do solo 653 $aClay content 653 $aFunções de pedotransferência 653 $aValidação do modelo 700 1 $aMACHADO, P. L. O. de A. 700 1 $aFIDALGO, E. C. C. 700 1 $aCOELHO, M. R. 700 1 $aMADARI, B. E. 773 $tGeoderma$gv. 139, n. 1/2, p. 90-97, Apr. 2007.
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